During shoulder arthroplasty the native functionality of the diseased shoulder joint is restored, this functionality is strongly dependent upon the native anatomy of the pre-diseased shoulder joint. Therefore, surgeons often use the healthy contralateral scapula to plan the surgery, however in bilateral diseases such as osteoarthritis this is not always feasible. Virtual reconstructions are then used to reconstruct the pre-diseased anatomy and plan surgery or subject-specific implants. In this project, we develop and validate a statistical shape modeling method to reconstruct the pre-diseased anatomy of eroded scapulae with the aim to investigate the existence of predisposing anatomy for certain shoulder conditions. The training dataset for the statistical shape model consisted of 110 CT images from patients without observable scapulae pathologies as judged by an experienced shoulder surgeon. 3D scapulae models were constructed from the segmented images. An open-source non-rigid B-spline-based registration algorithm was used to obtain point-to-point correspondences between the models. The statistical shape model was then constructed from the dataset using principle component analysis. The cross-validation was performed similarly to the procedure described by Plessers et al. Virtual defects were created on each of the training set models, which closely resemble the morphology of glenoid defects according to the Wallace classification method. The statistical shape model was reconstructed using the leave-one-out method, so the corresponding training set model is no longer incorporated in the shape model. Scapula reconstruction was performed using a Monte Carlo Markov chain algorithm, random walk proposals included both shape and pose parameters, the closest fitting proposal was selected for the virtual reconstruction. Automatic 3D measurements were performed on both the training and reconstructed 3D models, including glenoid version, critical shoulder angle, glenoid offset and glenoid center position. The root-mean-square error between the measurements of the training data and reconstructed models was calculated for the different severities of glenoid defects. For the least severe defect, the mean error on the inclination, version and critical shoulder angle (°) was 2.22 (± 1.60 SD), 2.59 (± 1.86 SD) and 1.92 (± 1.44 SD) respectively. The reconstructed models predicted the native glenoid offset and centre position (mm) an accuracy of 0.87 (± 0.96 SD) and 0.88 (± 0.57 SD) respectively. The overall reconstruction error was 0.71 mm for the reconstructed part. For larger defects each error measurement increased significantly. A virtual reconstruction methodology was developed which can predict glenoid parameters with high accuracy. This tool will be used in the planning of shoulder surgeries and investigation of predisposing scapular morphologies

In order to evaluate the relationship between acetabular and proximal femoral alignment in the initiation and evolution of osteoarthritis of the dysplastic hip, the acetabular and femoral angles were calculated geometrically from radiographs of 62 patients with pre-arthrosis and early osteoarthritis. The sum of the lateral opening angle of the acetabulum and the neck-shaft angle was defined as the lateral instability index (LII), and the sum of the anterior opening angle of the acetabulum and the anteversion angle of the femoral neck as the anterior instability index (AII). These two indices were compared in dysplastic and unaffected hips. A total of 22 unilateral hips with pre-arthrosis were followed for at least 15 years to determine whether the two indices were associated with the progression of osteoarthritis.

The LII of the affected hips (197.4 (sd 6.0)) was significantly greater than that of the unaffected hips (1830 (sd 6.9)). A follow-up study of 22 hips with pre-arthrosis showed that only the LII was associated with progression of the disease, and an LII of 196 was the threshold value for this progression.

Our aim was to investigate the relationship between urinary excretion of deoxypyridinoline (DPD) as a marker of bone resorption, and Perthes’ disease. There were 39 children with Perthes’ disease in the florid stage who collected first-morning urine samples at regular intervals of at least three months. The level of urinary DPD was analysed by chemiluminescence immunoassay and was correlated with the radiological stage of the disease as classified by Waldenström, and the severity of epiphyseal involvement according to the classification systems of Catterall and Herring. The urinary DPD levels of a group of 44 healthy children were used as a control.

The median urinary DPD/creatinine (CREA) ratio was significantly reduced (p < 0.0001) in the condensation stage and increased to slightly elevated values at the final stage (p = 0.05) when compared with that of the control group. Herring-C patients showed significantly lower median DPD/CREA ratios than Herring-B patients (p = 0.03). The significantly decreased median DPD/CREA ratio in early Perthes’ disease indicated a reduced bone turnover and supports the theory of a systemic aetiology. Urinary levels of DPD may therefore be used to monitor the course of Perthes’ disease.